When advertising on electronic media, advertisers and advertising agencies are able to receive immediate feedback as to the performance of their campaigns, based on how successful the creatives are in generating responses (such as clicks-visitors clicking on a banner advertisement to visit the advertiser's site—or post-click actions, such as making a purchase, signing up for a newsletter, joining a club, etc.). Further, these advertisers and agencies have significant flexibility in their ability to simultaneously run multiple advertisements (also called creative messages or creatives) within a campaign and to introduce new advertisements into an ongoing campaign. In particular, the advertiser or agency can exploit the placement allocation capabilities of ad servers to adjust the proportion of impressions in a campaign allocated to each advertisement. Even when one campaign ends and the next begins, the distinction between campaigns is oftentimes more contractual than defined by any difference in the creative messages comprising the campaigns. Therefore, a sequence of advertising campaigns can be thought of as one campaign in which the set of creative messages evolves as the advertiser or agency withdraws creatives that are no longer relevant or perform poorly and introduces new creatives. The decisions to withdraw old creative and introduce new creative are based on business decisions (such as the introduction of a new kind of marketing offer) or the performance of the creatives. The flexibility to add and withdraw creative and to adjust impression allocation across creatives provides advertisers and agencies with the opportunity to significantly enhance the performance of their advertising campaigns by diverting impressions to the better performing advertisements at the expense of the poorer performing advertisements.
Currently, when making performance-based decisions to withdraw or add creative from or to a campaign, advertisers and agencies have very little to guide them. While it is clear which of the existing creatives are performing poorly and are thus candidates for withdrawal, it is not clear what aspects of the successful creatives drive their success and hence should be considered for replication in new creatives. While long-time advertisers may develop some intuition for the types of creatives that are successful for them, this type of knowledge is by nature imprecise, hard to codify and maintain, and difficult to use to good advantage. Thus, the success or failure of new creative tends to be very much a random process. Likewise, the process of determining the allocation of impressions to advertisements is manual, tedious, imprecise and arbitrary. Typically, the advertiser or agency will review the performance of the advertising campaign on an infrequent basis and will adjust the allocations of impressions to advertisements in an arbitrary and not well-founded manner based on ad hoc rules. Even when the rules for allocating impressions to advertisements have some reasonable basis, these rules tend not to take advantage of all the information available from the performance data and tend to be applied only sporadically. These practices result in failure to achieve or even approach optimal campaign performance.
In many campaigns the likelihood that a visitor responds to an advertisement is driven by the particular elements (“attribute values”) that comprise that advertisement. This insight could be used to provide information about successful attributes and values for use in determining which advertisements to show in order to increase the overall campaign performance. However, currently advertisers and agencies have no tools or methods that give them access to this type of analysis and knowledge, and hence the potential campaign performance improvements are inaccessible.